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The original Blade Runner was released in 1982. It depicts a future in which synthetic humans known as replicants are bioengineered by a powerful Corporation to work on off-world colonies. The final scene stands out because of the “tears in rain” speech given by Roy, the dying replicant.

I’ve seen things you people wouldn’t believe. Attack ships on fire off the shoulder of Orion. I watched C-beams glitter in the dark near the Tannhäuser Gate. All those moments will be lost in time, like tears in rain. Time to die.

This was the moment in which the artificial human had begun to think for himself. But what makes this so relevant is that the film is predicting what life will be like in 2019. And with 2018 only a few days away, 2019 is no longer science fiction, and neither is Artificial Intelligence (AI).

Artificial Intelligence and machine learning

There is no one single agreed upon definition for AI, “machine learning” on the other hand is a field of computer science that enables computers to learn without being explicitly programmed. The way it does this is by analysing large amounts of data in order to make accurate predictions, for example regression analysis does something very similar when using data to produce a line of best fit.

The problem with the term artificial intelligence is the word intelligence, defining this is key. If intelligence is, the ability to learn, understand, and make judgments or have opinions based on reason, then you can see how difficult deciding if a computer has intelligence might be. So, for the time being think of it like this:

AI is the intelligence; machine learning is the enabler making the machine smarter i.e. it helps the computer behave as if it is making intelligent decisions.

AI in education

As with many industries AI is already having an impact in education but given the right amount of investment it could do much more, for example

Teaching – Freeing teachers from routine and time-consuming tasks like marking and basic content delivery. This will give them time to develop greater class engagement and address behavioural issues and higher-level skill development. These being far more valued by employers, as industries themselves become less reliant on knowledge but dependant on those who can apply it to solve real word problems. In some ways AI could be thought of as a technological teaching assistant. In addition the quality and quantity of feedback the teacher will have available to them will not only be greatly improved with AI but be far more detailed and personalised.

Learning – Personalised learning can become a reality by using AI to deliver a truly adaptive experience. AI will be able to present the student with a personalised pathway based on data gathered from their past activities and those of other students. It can scaffold the learning, allowing the students to make mistakes sufficient that they will gain a better understanding. AI is also an incredibly patient teacher, helping the student learn from constant repetition, trial and error.

Assessment and feedback – The feedback can also become rich, personalised and most importantly timely. Offering commentary as to what the individual student should do to improve rather than the bland comments often left on scripts e.g. “see model answer” and “must try harder.” Although some teachers will almost certainly mark “better” than an AI driven system would be capable of, the consistency of marking for ALL students would be considerably improved.

Chatbots are a relatively new development that use AI. In the Autumn of 2015 Professor Ashok Goel built an AI teaching assistant called Jill Watson using IBM’s Watson platform. Jill was developed specifically to handle the high number of forum posts, over 10,000 by students enrolled on an online course. The students were unable to tell the difference between Jill and a “real” teacher. Watch and listen to Professor Goel talk about how Jill Watson was built.

AI still has some way to go, and as with many technologies although there is much talk, getting it into the mainstream takes time and most importantly money. Although investors will happily finance driverless cars, they are less likely to do the same to improve education.

The good news is that Los Angeles is still more like La La Land than the dystopian vision created by Ridely Scott, and although we have embraced many new technologies, we have avoided many of the pitfalls predicated by the sci-fi writers of the past, so far at least.

But we have to be careful watch this, it’s a robot developed by AI specialist David Hanson named “Sophia” and has made history by becoming the first ever robot to be granted a full Saudi Arabian citizenship, honestly…..

We are in the season when many learning and technology leaders gather to discuss what’s new and what’s trending in the world of education. And at two recent conferences, Learning Technologies and EdTechXEurope there was plenty to see. Generally, the role of technology in learning seems to have found its place with many acknowledging it should support learning not drive it. However it’s still very easy to look at the latest shiny new offerings and think, this is great how can I use it, rather than, what learning problem does it solve.

Here are a few of the most notable developments.

1. Video is getting even better – fuelled by the YouTube generation of learners, those who would rather watch a video than read a book as a means to consume knowledge, we have some new developments.

Firstly, using video to deliver micro learning. Not just small chunks of video but untethered, JIT, 3 minute courses that offer the learner digestible easy to remember information. Think of micro learning as a series of very short courses that could be linked to each other or not, and can even include assessment.

Secondly, interactive video. TV is no longer the all commanding medium it once was, it like other technologies has had to evolve. In recent years the shift has been towards better engagement, offering spin off programmes where there is a live audience, web sites that showcase the backstory to the characters and programmes that require the audience to vote and so influence events. Now we have interactive video, where the individual can choose what they would do and so change the future. Check out this amazing example, used by Deloitte to attract new talent.

2.Gamificationis becoming better understood. For the uninitiated gamification is the use of game based principles to improve motivation, concentration and more effective learning. Gamification uses Points (P) as a measure of reward, Badges (B) as a visual record of success, and leader boards (L) to create competition.

We now believe Dopamine, the pleasure induced neurotransmitter (chemical) is not created as a result of a reward e.g. by being given a badge, it is the challenge and subsequent achievement that releases the dopamine which in turn leads to pleasure. This might seem obvious, with hindsight, no one gets pleasure from being top of a leader board, if they did nothing to get there. In addition, dopamine is released when you have a new experience, so think about changing pathways, setting different questions and tasks, it’s certainly not very motivational to go over the same content again.

3. Information overload is leading to a need for Knowledge Curation – we are living in an age where information is abundant. You can learn anything from the internet. But there lies the problem, we have too much information, we suffer from information overload. Curation is the collecting and sorting of meaningful content around a theme, and it is now in some instances being thought of as more valuable than the content itself.

Arguably curation is not so much about what you curate and share but what you don’t share. In addition to the organisation of content the curators need to have an expertise in the subject and an understanding of their audience and what they want.

Steven Rosenbaum in his book Curation Nation, offers up a good summary. “Curation replaces noise with clarity. And it’s the clarity of your choosing; it’s the things that people you trust help you find.”

4. The market is becoming more accepting of user generated content (UGC) – organisations are beginning to see the benefits of UGC for a whole host of reasons. It’s a very fast way of generating content, there is a lot of expertise that can be uncovered by allowing individuals to share what they know, it’s often user friendly, and importantly its cheap. It is of course not perfect, and there are concerns about quality, but by allowing the users to rate the content, the quality might just look after itself.

5.Virtual reality (VR), Augmented Reality (AR) and Artificial intelligence (AI) – not that these are all related, but just a simple way of me summarising three areas to keep an eye on in the not too distant future. All of these technologies are becoming cheaper, largely because of the investment made and experience being gained in the gaming industry.

By way of a footnote Google have released an open source software called Tensorflow which can help with machine learning, something that they believe will help drive new initiatives in AI.